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Record W2784801814 · doi:10.16910/jemr.10.6.1

Abstracts of the 19th European Conference on Eye Movements 2017

2017· article· en· W2784801814 on OpenAlexfundno aff
Ralph Radach, Heiner Deubel, Christian Vorstius, Markus Hofmann

Bibliographic record

VenueJournal of Eye Movement Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdenosine and Purinergic Signaling
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaNational Science FoundationCanadian Institutes of Health ResearchCentre National de la Recherche ScientifiqueUniversity of MelbourneMedical Research CouncilUniversité de LyonInstitut National de la Santé et de la Recherche MédicaleDeutsche ForschungsgemeinschaftMcGill UniversityAmerican Association of University WomenNational Institutes of Health
KeywordsEye movementLate 19th centuryOptometryArtificial intelligenceComputer scienceMedicineArtAestheticsPeriod (music)

Abstract

This document contains all abstracts of the 19th European Conference on Eye Movements, August 20-24, 2017, in Wuppertal, Germany

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: fund_new · design weight: 1678.90 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: other
about Canada: no
confidence: low

A compiled volume of abstracts from a domain eye-movement conference; a collection of research reports, not a study of research.

GPT-5.6 (high)OUT
genre: other
about Canada: no
confidence: high

It is a collection of conference abstracts about eye-movement research, not a study of research itself.

Grok 4.5OUT
genre: other
about Canada: no
confidence: high

Compiled conference abstracts on eye-movement science; domain proceedings dump, not a study of research practice.

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.232
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0060.002
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2320.152

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.102
GPT teacher head0.401
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2017
Admission routes1
Has abstractyes

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